Researches On Modeling And Solving Of Production Scheduling For Process Industry Based On Saving Energy

Process industry is the backbone industry of national economy of a country, it holds the balance of national economy. Production scheduling is the headquarters of production running in a process enterprise. Improving the quality and efficiency of production scheduling plays an important role in improving economic and social benefits of a process enterprise. Energy is an important factor in the production of process industry. It not only influences the benefits of enterprises, but also has great relationship with the social duty of enterprises. Under the domestic and overseas circumstance with the lack of energy and the rising of the price day by day, it is very important to carry out the research on production scheduling with minimizing the energy consumption in process industry, especially in metallurgy industry. This paper is based on the project called the research on the method of process industry's pattern recognition, optimization search and scheduling which is a part of the important national natural science fund project: the research on theory and method of metallurgy process control. The project serial is 60634020.This paper researches on the multi-product batch processing scheduling problem which widely exits in process industry and addresses some typical problems of it, such as model, algorithm and practical application. The major researched aspects are listed as follows:1. Researches on the hybrid flow shop scheduling problem with minimizing the energy consumption. This problem is solved by genetic algorithm. For improving the performance of the simple genetic algorithm, a self-adaptive mutation is addressed and the experiment proves that the improved genetic algorithm is better than the simple genetic algorithm.2. Designs the method of partitioning the batch to the multi-product batch processing scheduling problem; Builds the mathematical model with minimizing the energy consumption, considering all kinds of constraints under the circumstance of exiting middle storage.3. Addresses the improved Memetic algorithm which uses genetic algorithm as basic frame and embeds simulated annealing algorithm and tabu algorithm; Designs the operators of the three algorithms for multi-product batch processing scheduling problem.4. Solves the multi-product batch processing scheduling problem in aluminum industry using improved Memetic algorithm, and compares the results with the one using the genetic algorithm so that the advantage of improved Memetic algorithm is clear.At last, the work of this paper is summarized and the prospective of future research on model and algorithm of process industry's scheduling problem is discussed.